Adaptive charts with sampling at fixed times under non-normality

Abstract Recently developed adaptive charts have been shown to give substantially faster detection of most process shifts than the fixed parameters charts. The “sampling at fixed times” idea can be implemented in the adaptive control charts, and from the practical viewpoint, the adaptive charts with sampling at fixed times are considered to be more convenient to administer than the traditional adaptive charts. The usual assumption for designing the control chart is that the data or measurements are normally distributed. However, this assumption may not be tenable in some production processes. The Burr distribution has been used in the literature to represent various non-normal distributions. In the present paper, the Burr distribution is employed to evaluate the adaptive charts with sampling at fixed times for non-normal populations. Base on the study, it is shown that the variable sampling interval with fixed times (VSIFT) chart and variable sampling rate with fixed times (VSRFT) chart are very sensitive to non-normality; however, the variable parameters with fixed times (VPFT) chart is relatively robust against non-normality. Under consideration of false alarm rate and the ability to detect mean shifts, the VPFT chart is a more appropriate tool for non-normal populations.

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